Visualization Tutorial — Droplet Surface and Contact Angle

This tutorial demonstrates how to visualize a droplet and compute its contact angle using the wetting_angle_kit package. We’ll use the slicing contact angle method and visualize the resulting droplet with the DropletSlicePlotter class.

1. Overview

The visualization workflow involves the following steps:

Parse atomic positions from a trajectory file.
Identify water molecules (oxygen and hydrogen atoms).
Compute the droplet surface and contact angle using the slicing method.
Visualize the droplet, fitted circle, tangent, and wall.

2. Import Required Modules

import numpy as np
from wetting_angle_kit.parsers import (
    LammpsDumpParser,
    LammpsDumpWaterFinder,
    LammpsDumpWallParser,
)
from wetting_angle_kit.analysis.slicing import SlicingFrameFitter
from wetting_angle_kit.visualization import DropletSlicePlotter

3. Define the Input Trajectory

filename = (
    "../wetting_angle_kit/tests/trajectories/traj_10_3_330w_nve_4k_reajust.lammpstrj"
)

4. Identify Water Molecules

wat_find = LammpsDumpWaterFinder(
    filename, particle_type_wall={3}, oxygen_type=1, hydrogen_type=2
)

oxygen_indices = wat_find.get_water_oxygen_ids(frame_index=0)
print("Number of water molecules detected:", len(oxygen_indices))

5. Parse Atomic Coordinates

parser = LammpsDumpParser(filepath=filename)
oxygen_position = parser.parse(frame_index=10, indices=oxygen_indices)

# Wall parser: ``liquid_particle_types`` lists everything the parser
# should *exclude* (so that what remains are the wall atoms).
coord_wall = LammpsDumpWallParser(filename, liquid_particle_types=[1, 2])
wall_coords = coord_wall.parse(frame_index=10)

6. Compute Contact Angles

processor = SlicingFrameFitter(
    liquid_coordinates=oxygen_position,
    liquid_geom_center=np.mean(oxygen_position, axis=0),
    droplet_geometry="cylinder_y",
    delta_cylinder=5,
    max_dist=100,
)

list_angles, array_surfaces, array_popt = processor.predict_contact_angle()
print("Mean contact angles (°):", list_angles)

7. Visualize the Droplet

plotter = DropletSlicePlotter(center=True)

# ``predict_contact_angle`` returns three parallel lists (one entry per
# slice that produced a usable angle); pick a single index across all
# three so the overlay refers to one and the same slice.
slice_idx = 0
fig = plotter.plot_surface_points(
    oxygen_position=oxygen_position,
    surface_data=[array_surfaces[slice_idx]],
    popt=array_popt[slice_idx],
    wall_coords=wall_coords,
    alpha=list_angles[slice_idx],
)

# Interactive view in a notebook
fig.show()

# Or save a standalone HTML page
fig.write_html("droplet_plot.html")
print("Plot saved as 'droplet_plot.html'")